JAM Image Dataset
Versions
22. Rebalance: 296:110:94
v26
May 8, 2022
21. Augm_12: Noise: 350:70:10
v25
May 7, 2022
2022-05-08 4:30am
v24
May 7, 2022
20. Rebalance basic: 350:87:63
v23
May 7, 2022
19. Augm_11: cutout-shear-rotation
v22
May 4, 2022
18. Augm_10: Blue-saturation-crop
v21
May 4, 2022
17. Augm_9: Exposure-Rotation-Brightness
v20
May 4, 2022
16. Augm_8: Shear-Noise-mosiac
v19
May 4, 2022
15. Augm_7: Noise:420:70:10
v18
May 3, 2022
14. Rebalance Basic: 420:73:7
v17
May 3, 2022
13. Rebalance Basic: 420:65:15
v16
May 3, 2022
12. Augm_6: Mosaic-Hue-Rotation: 420:70:10
v15
May 3, 2022
11. Rebalance Basic: 420:38:42
v14
Apr 20, 2022
10. Rebalance Basic: 420:70:10
v13
Apr 20, 2022
9. Rebalance Basic: 420:70:10
v12
Apr 20, 2022
8. No Change: Remapped to 13 Classes
v11
Apr 19, 2022
7. Augm_5: Rotation-Noise-Saturation
v10
Apr 11, 2022
6. Augm_4: Shear-Brightness-Noise-Reflect-416
v9
Apr 11, 2022
6. Augm_3: Flip-Rotate-Crop-With-Validation-No-Test-Stretch-to-416
v8
Apr 11, 2022
5. Augm_2: Flip-Rotate-Crop-With-Validation-No-Test
v7
Apr 10, 2022
4. Yolov5
v6
Apr 9, 2022
3. Augm_1: Flip-Rotate-Crop
v4
Apr 9, 2022
2. Basic 500 Images Resized to 416 By 416
v2
Apr 9, 2022
v25
21. Augm_12: Noise: 350:70:10
Generated on May 7, 2022
Popular Download Formats
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
920 Total Images
View All Images
Dataset Split
Train Set 91%
840Images
Valid Set 8%
70Images
Test Set 1%
10Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (white edges) in 416x416
Modify Classes: 14 remapped, 0 dropped
Augmentations
Outputs per training example: 2
Noise: Up to 8% of pixels
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